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Machine Learning Engineering  with Python - Second Edition

You're reading from  Machine Learning Engineering with Python - Second Edition

Product type Book
Published in Aug 2023
Publisher Packt
ISBN-13 9781837631964
Pages 462 pages
Edition 2nd Edition
Languages
Author (1):
Andrew P. McMahon Andrew P. McMahon
Profile icon Andrew P. McMahon

Table of Contents (12) Chapters

Preface 1. Introduction to ML Engineering 2. The Machine Learning Development Process 3. From Model to Model Factory 4. Packaging Up 5. Deployment Patterns and Tools 6. Scaling Up 7. Deep Learning, Generative AI, and LLMOps 8. Building an Example ML Microservice 9. Building an Extract, Transform, Machine Learning Use Case 10. Other Books You May Enjoy
11. Index

Setting up an AWS account

As previously stated, you don't have to use AWS, but that's what we're going to use throughout this book. Once it's set up here, you can use it for everything we'll do:

  1. To set up an AWS account, navigate to aws.amazon.com and select Create Account. You will have to add some payment details but everything we mention in this book can be explored through the free tier of AWS, where you do not incur a cost below some set threshold of consumption.
  2. Once you have created your account, you can navigate to the AWS Management Console, where you can see all of the services that are available to you (see Figure 2.5):

    Figure 2.5 – The AWS Management Console
  3. Finally, there would be no ML engineering without ML models. So, the final piece of software you should install is one that will help you track and serve your models in a consistent way. For this, we will use MLflow, an open source platform from Databricks and under the stewardship of...
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